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We first create a simple table, t1, populated with around 78,000 numbers: benchmark@ORA10G> create table t1 as 2 select rownum as x from all_objects 3 union all 4 select rownum as x from all_objects; Table created. benchmark@ORA10G> commit; Commit complete. benchmark@ORA10G> select count(*) from t1; 78228 We use the rownum pseudo column on the table all_objects (which usually has a decent number of rows) to populate table t1 with numbers. The rownum pseudo column returns a number for each row, indicating the order in which Oracle selected the row. The first row selected has a rownum value of 1, the second has a value of 2, and so on. Next, we create a PL/SQL package, prefetch_pkg, that contains a single procedure called get_details. We will use this package to demonstrate the CallableStatement bug and its workaround: benchmark@ORA10G> create or replace package prefetch_pkg 2 as 3 procedure get_details( p_num_of_rows in number, 4 p_sql_tag in varchar2, p_cursor in out sys_refcursor ); 5 end; 6 / Package created. The package body defines the procedure get_details. It simply returns a ref cursor containing values of column x for a given number of rows. It uses the rownum pseudo column to restrict the number of rows returned. Note that we also have a SQL tag in the parameter p_sql_tag, using which we tag the SQL within the PL/SQL with the fetch size information we set at the OracleConnection, CallableStatement, and ResultSet interface levels. This helps us identify the SQL in the tkprof output, which is the tool we ll use to peek at what really goes on internally for a given prefetch size: benchmark@ORA10G> create or replace package body prefetch_pkg 2 as 3 procedure get_details( p_num_of_rows in number, p_sql_tag in varchar2, 4 p_cursor in out sys_refcursor ) 5 is 6 begin 7 open p_cursor for

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There are several different technologies that support database transactions, including transactions in the database itself, ADO.NET, Enterprise Services, and System.Transactions. When updating a single database (even multiple tables), any of them will work fine, and your decision will often be based on which is fastest or easiest to implement. If your application needs to update multiple databases, however, the options are a bit more restrictive. Transactions that protect updates across multiple databases are referred to as distributed transactions. In SQL Server, you can implement distributed transactions within stored procedures. Outside the database, you can use Enterprise Services or System.Transactions. Distributed transaction technologies use the Microsoft Distributed Transaction Coordinator (DTC) to manage the transaction across multiple databases. There is a substantial performance cost

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In this chapter we have covered the following: What you need to do to deliver Axapta functionality and data over the Web Getting Enterprise Portal up and running How to use the Content Management System, articles, discussion forums, and polls

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to enlisting the DTC in a transaction. Your application, the DTC, and the database engine(s) all need to interact throughout the transactional process to ensure that a consistent commit or rollback occurs, and this interaction takes time. Historically, you had to pick one transactional approach for your application. This often meant using distributed transactions even when they weren t required and paying that performance cost. The new System.Transactions namespace offers a compromise through the TransactionScope object. It starts out using nondistributed transactions (like those used in ADO.NET), and thus offers high performance for most applications. However, as soon as your code uses a second database within a transaction, TransactionScope automatically enlists the DTC to protect the transaction. This means you get the benefits of distributed transactions when you need them, but you don t pay the price for them when they aren t needed. The data portal allows the developer to specify which transactional technology to use for each of a business object s data access methods. To do this, the message router portion of the data portal uses some extra classes, as shown in Figure 4-4. Notice that this is basically the same diagram as Figure 4-3, but with extra types to support the transactional technologies.

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